CHIKV scRNA-seq
Ryan Sheridan
2021-07-14
Quality control
Cell Ranger identified 17,356 cells.
The cutoff used by cellranger to identify cell-associated barcodes did not appear as accurate for sample AF2. To account for this AF2 cells were initially filtered to remove cells with <800 UMIs.
Cells were filtered to only include those with >250 and <6,000 detected genes and <20% mitochondrial counts. These filtering steps were not performed on CHIKV-high cells due to the possibility that the virus is affecting host transcription. 11,978 cells remained for downstream analysis after filtering.
Summary
The number of cells filtered from each sample is shown below. 
Cell Ranger
Cell Ranger metrics are shown for each sample.
Scatter plots
UMAPs
UMAP projections are shown for each replicate after filtering. Cells that appear to have a high percentage of mitochondrial reads are ones that harbor viral RNA and were not subjected to the final filtering steps.
After filtering cells, the raw counts for each gene were divided by the total counts for the cell, multiplied by a scaling factor (10,000), and log-transformed (NormalizeData). The top 2000 genes that show the most cell-to-cell variation were then identified (FindVariableFeatures) and the data were scaled to prevent highly expressed genes from biasing the downstream analysis (ScaleData). For clustering and visualizing differences between cells, PCA and UMAP were used to reduce the dimensionality of the dataset (RunPCA, RunUMAP).
UMAP projections are shown below with cells colored by sample ID, the mock- and CHIKV-infected samples show strong overlap.
UMAP projections are shown for cells divided by replicate, colors correspond to sample ID as shown above. The biological replicates show strong overlap and very similar overall structure, suggesting that batch effects are not impacting gene expression patterns.
UMAP projection shows 8 hpi and 24 hpi samples with cells colored by sample ID.
UMAP projection shows 8 hpi and 24 hpi samples with cells colored by sample ID. Cells from the 24 hpi samples are shown in grey.
UMAP projections are shown for 8 hpi cells divided by sample ID, 24 hpi cells are shown in grey.
Cell type annotation
To identify cell clusters, a k-nearest neighbors graph was generated using the first 40 principal components (FindNeighbors). This graph was then used to iteratively group cells together using the Louvain method (FindClusters).
Broad cell types were first assigned by comparing gene expression patterns for each cluster with data available from Immgen (clustify). UMAPs below show cell type annotations for different clustering resolutions, the number of distinct clusters is shown in parenthesis.
